There are many instances where it is desirable to have a system capable of receiving information from a particular signal source where the environment includes sources of interference signals at locations different from that of the information signal source. For discussion purposes, the specific instances will be generalized to the extent possible. Turning first to FIG. 1, a block diagram of a sound processing system 10 is shown. The system 10 includes at least one microphone 12 that picks up sounds from a sound field in which it is located and converts these sounds to electrical signals. In the present case, a plurality of microphones are depicted and the microphones are numbered from one to N1. The electrical signals from the microphones 12 are preferably input to an audio processor 14. The sounds are to be reproduced by one or more output devices 16 such as loudspeakers, earphones, and the like. The sound can optionally pass through transmission channels or additional processing before arriving at the output device 16. It may even be recorded and played back before arriving at the output device 16.
In general, the sound field into which the system 10 is placed contains not only the sounds to be picked up, referred to as a utility signal, but also unwanted sounds, referred to as noise or noise signals. In these situations, it is desirable to process the signals picked up by the microphones 12 in order to reduce the noise contents electronically. There are several conventional methods for reducing the noise electronically through the audio processor 14. One is known as static beamforming where the signals from two or more microphones are passed through filters and combined to form a single signal. The resulting signal will show a sensitivity to sounds that depends upon the direction of the sound incidence as compared to the direction of the microphone assembly. The directivity response will take the form of one or more beams. Due to the fact that the lobes of the directivity response have different magnitudes, the beamformer will show a signal to noise improvement when the beam is oriented so that the utility signal falls within the main lobe and the main part of the noise falls outside the main lobe. Static beamformers have the disadvantage that, in order to provide substantial noise reduction under general noise conditions, a large number of microphones are required.
Another conventional method is known as adaptive beamforming which is achieved when the filters of a beamformer are variable and controlled by an adaptation process. Normally such an adaptation process works to minimize the output signal power. An adaptive beamformer can track noise sources and dynamically adjust the directivity response such that the sensitivity at the direction of the noise incidence is minimized while keeping the sensitivity at the utility direction high. Currently known adaptive beamformers show the disadvantage that they are only capable of tracking a limited number of noise sources, mostly only a single. Furthermore adaptive beamformers work with a fairly large time constant in the adaptation process. Therefore they are only able to track quasi-static noise sources.
Yet other conventional methods apply only to a single microphone multiband noise reduction situation, that is, spectral subtraction. When only a single microphone signal is available, it is not possible to obtain information as to the direction of sound incidence from the microphone signal and it is therefore not possible to perform beamforming as above. Still a reduction of the noise contents can be achieved under these circumstances. Such methods all rely on dividing the signal into a number of frequency bands. In each band the signal is analyzed statistically to derive measures of the utility signal and noise content. Based on these measures a band gain is derived and applied that amplifies bands with utility signal contents while attenuating bands with noise contents. Unfortunately, the statistical analysis requires long time constants. Therefore the single microphone methods are limited to a sound field with stationary noise signals and non-stationary utility signals.
Further conventional methods are known that use two microphones and analyze the microphone signal contents to derive and apply a gain in frequency bands. The gain is a function of how the microphone signals relate to each other. The known methods have the disadvantage that they only work when the signal in each frequency band consists of either utility signal or noise and not when a combination of utility signal and noise is present.
By contrast to the conventional methods above, the present invention uses a different approach to the problem. It uses the general equations for sound fields to analyze the microphone signals and find required properties of one or more components or waves contained in the input signals. The desired properties can for example be the direction of sound incidence or the pressure gradient of the impinging waves. The incoming waves are amplified with a gain function based on these properties, that is, the directivity or the gradient. Based on the amplified waves an output signal is generated either by synthesizing the amplified waves or by applying filtering to an input signal combination. The present invention can operate in a number of applications including hearing aids, directional microphones, microphone arrays, silicon microphone assemblies, headsets, hearing protectors, cordless phones, mobile phones, camcorders, personal computers, laptops, palmtops, and personal digital assistants, among others. In some embodiments, the present invention is especially suited to work with head worn microphones that pick up the speech signal of the wearer. In this application, the present invention offers a substantially improved noise reduction when compared to conventional solutions with comparable sound quality.